Cocrystal Prediction of Nifedipine Based on the Graph Neural Network and Molecular Electrostatic Potential Surface.

Nifedipine (NIF) is a dihydropyridine calcium channel blocker primarily used to treat conditions such as hypertension and angina. However, its low solubility and low bioavailability limit its effectiveness in clinical practice. Here, we developed a cocrystal prediction model based on Graph Neural Networks (CocrystalGNN) for the screening of cocrystals with NIF. And scoring 50 coformers using CocrystalGNN. To validate the reliability of the model, we used another prediction method, Molecular Electrostatic Potential Surface (MEPS), to verify the prediction results. Subsequently, we performed a second validation using experiments. The results indicate that our model achieved high performance. Ultimately, cocrystals of NIF were successfully obtained and all cocrystals exhibited better solubility and dissolution characteristics compared to the parent drug. This study lays a solid foundation for combining virtual prediction with experimental screening to discover novel water-insoluble drug cocrystals.

Directed-evolution mutations enhance DNA-binding affinity and protein stability of the adenine base editor ABE8e.

Adenine base editors (ABEs), consisting of CRISPR Cas nickase and deaminase, can chemically convert the A:T base pair to G:C. ABE8e, an evolved variant of the base editor ABE7.10, contains eight directed evolution mutations in its deaminase TadA8e that significantly increase its base editing activity. However, the functional implications of these mutations remain unclear. Here, we combined molecular dynamics (MD) simulations and experimental measurements to investigate the role of the directed-evolution mutations in the base editing catalysis. MD simulations showed that the DNA-binding affinity of TadA8e is higher than that of the original deaminase TadA7.10 in ABE7.10 and is mainly driven by electrostatic interactions. The directed-evolution mutations increase the positive charge density in the DNA-binding region, thereby enhancing the electrostatic attraction of TadA8e to DNA. We identified R111, N119 and N167 as the key mutations for the enhanced DNA binding and confirmed them by microscale thermophoresis (MST) and in vivo reversion mutation experiments. Unexpectedly, we also found that the directed mutations improved the thermal stability of TadA8e by ~ 12 °C (Tm, melting temperature) and that of ABE8e by ~ 9 °C, respectively. Our results demonstrate that the directed-evolution mutations improve the substrate-binding ability and protein stability of ABE8e, thus providing a rational basis for further editing optimisation of the system.

Accelerating electrostatic particle-in-cell simulation: A novel FPGA-based approach for efficient plasma investigations.

Particle-in-cell (PIC) simulation serves as a widely employed method for investigating plasma, a prevalent state of matter in the universe. This simulation approach is instrumental in exploring characteristics such as particle acceleration by turbulence and fluid, as well as delving into the properties of plasma at both the kinetic scale and macroscopic processes. However, the simulation itself imposes a significant computational burden. This research proposes a novel implementation approach to address the computationally intensive phase of the electrostatic PIC simulation, specifically the Particle-to-Interpolation phase. This is achieved by utilizing a high-speed Field Programmable Gate Array (FPGA) computation platform. The suggested approach incorporates various optimization techniques and diminishes memory access latency by leveraging the flexibility and performance attributes of the Intel FPGA device. The results obtained from our study highlight the effectiveness of the proposed design, showcasing the capability to execute hundreds of functional operations in each clock cycle. This stands in contrast to the limited operations performed in a general-purpose single-core computation platform (CPU). The suggested hardware approach is also scalable and can be deployed on more advanced FPGAs with higher capabilities, resulting in a significant improvement in performance.

A new strategy to improve the quality of frozen chicken wings: High voltage electrostatic field combined with phosphorus-free water retaining agent.

Freezing is a commonly used method for long-term storage of chicken wing products, of which disadvantages are mainly the product damage caused in the process. The aim of this study was to improve the freezing quality of chicken wings with a combination of phosphorus-free water retaining agent (WRA) and high-voltage electrostatic field (HVEF). The effect of WRA acting at different HVEF intensities (0, 1, 3, and 5 kV/cm) on the quality attributes of frozen chicken wings was investigated in 0, 7, 14, 21, 28 and 35 days of frozen storage. The results showed that WRA had functional properties of significantly improving the water holding capacity (WHC), color and texture properties, and fat stability of frozen chicken wing samples. The application of HVEF on this basis helped to promote the absorption of WRA and inhibit oxidative deterioration of chicken wing samples during frozen storage. Meanwhile, the combination of HVEF at 3 kV/cm was more prominent in terms of improvement in WHC, moisture content, color, protein secondary structure and microstructure integrity. This advantage had been consistently maintained with the extension of storage time. Overall, WRA combined with HVEF of 3 kV/cm can be used as an effective strategy to improve the freezing quality of chicken wing samples and has the potential to maintain the frozen chicken wing samples quality for a long time.

Self-Assembly of Molecular Landers Equipped with Functional Moieties on the Surface: A Mini Review.

The bottom-up fabrication of supramolecular and self-assembly on various substrates has become an extremely relevant goal to achieve prospects in the development of nanodevices for electronic circuitry or sensors. One of the branches of this field is the self-assembly of functional molecular components driven through non-covalent interactions on the surfaces, such as van der Waals (vdW) interactions, hydrogen bonding (HB), electrostatic interactions, etc., allowing the controlled design of nanostructures that can satisfy the requirements of nanoengineering concepts. In this context, non-covalent interactions present opportunities that have been previously explored in several molecular systems adsorbed on surfaces, primarily due to their highly directional nature which facilitates the formation of well-ordered structures. Herein, we review a series of research works by combining STM (scanning tunneling microscopy) with theoretical calculations, to reveal the processes used in the area of self-assembly driven by molecule Landers equipped with functional groups on the metallic surfaces. Combining these processes is necessary for researchers to advance the self-assembly of supramolecular architectures driven by multiple non-covalent interactions on solid surfaces.

Molecular interactions of the Omicron, Kappa, and Delta SARS-CoV-2 spike proteins with quantum dots of graphene oxide.

CONTEXT: The Omicron, Kappa, and Delta variants are different strains of the SARS-CoV-2 virus. Graphene oxide quantum dots (GOQDs) represent a burgeoning class of oxygen-enriched, zero-dimensional materials characterized by their sub-20-nm dimensions. Exhibiting pronounced quantum confinement and edge effects, GOQDs manifest exceptional physical-chemical attributes. This study delves into the potential of graphene oxide quantum dots, elucidating their inherent properties pertinent to the surface structures of SARS-CoV-2, employing an integrated computational approach for the repositioning of inhibitory agents. METHODS: Following rigorous adjustment tests, a spectrum of divergent bonding conformations emerged, with particular emphasis placed on identifying the conformation exhibiting optimal adjustment scores and interactions. The investigation employed molecular docking simulations integrating affinity energy evaluations, electrostatic potential clouds, molecular dynamics encompassing average square root calculations, and the computation of Gibbs-free energy. These values quantify the strength of interaction between GOQDs and SARS-CoV-2 spike protein variants. The receptor structures were optimized using the CHARM-GUI server employing force field AMBERFF14SB. The algorithm embedded in CHARMM offers an efficient interpolation scheme and automatic step size selection, enhancing the efficiency of the optimization process. The 3D structures of the ligands are constructed and optimized with density functional theory (DFT) method based on the most stable conformer of each binder. Autodock Vina Software (ADV) was utilized, where essential parameters were specified. Electrostatic potential maps (MEPs) provide a visual depiction of molecules' charge distributions and related properties. After this, molecular dynamics simulations employing the CHARM36 force field in Gromacs 2022.2 were conducted to investigate GOs' interactions with surface macromolecules of SARS-CoV-2 in an explicit aqueous environment. Furthermore, our investigation suggests that lower values indicate stronger binding. Notably, GO-E consistently showed the most negative values across interactions with different variants, suggesting a higher affinity compared to other GOQDs (GO-A to GO-D).

Charge block-driven liquid-liquid phase separation - mechanism and biological roles.

Liquid-liquid phase separation (LLPS) has increasingly been found to play pivotal roles in a number of intracellular events and reactions, and has introduced a new paradigm in cell biology to explain protein-protein and enzyme-ligand interactions beyond conventional molecular and biochemical theories. LLPS is driven by the cumulative effects of weak and promiscuous interactions, including electrostatic, hydrophobic and cation-π interactions, among polypeptides containing intrinsically disordered regions (IDRs) and describes the macroscopic behaviours of IDR-containing proteins in an intracellular milieu. Recent studies have revealed that interactions between 'charge blocks' - clusters of like charges along the polypeptide chain - strongly induce LLPS and play fundamental roles in its spatiotemporal regulation. Introducing a new parameter, termed 'charge blockiness', into physicochemical models of disordered polypeptides has yielded a better understanding of how the intrinsic amino acid sequence of a polypeptide determines the spatiotemporal occurrence of LLPS within a cell. Charge blockiness might also explain why some post-translational modifications segregate within IDRs and how they regulate LLPS. In this Review, we summarise recent progress towards understanding the mechanism and biological roles of charge block-driven LLPS and discuss how this new characteristic parameter of polypeptides offers new possibilities in the fields of structural biology and cell biology.

Exploring Biomolecular Conformational Dynamics with Polarizable Force Field AMOEBA and Enhanced Sampling Method Milestoning.

Conformational dynamics play a crucial role in determining the behavior of the biomolecules. Polarizable force fields, such as AMOEBA, can accurately capture electrostatic interactions underlying the conformational space. However, applying a polarizable force field in molecular dynamics (MD) simulations can be computationally expensive, especially in studying long-time-scale dynamics. To overcome this challenge, we incorporated the AMOEBA potential with Milestoning, an enhanced sampling method in this work. This integration allows us to efficiently sample the rare and important conformational states of a biomolecule by using many short and independent molecular dynamics trajectories with the AMOEBA force field. We applied this method to investigate the conformational dynamics of alanine dipeptide, DNA, and RNA A-B form conversion. Well-converged thermodynamic and kinetic properties were obtained, including the free energy difference, mean first passage time, and critical transitions between states. Our results demonstrate the power of integrating polarizable force fields with enhanced sampling methods in quantifying the thermodynamic and kinetic properties of biomolecules at the atomic level.

Binding energies and hydrogen bonds effects on DNA-cisplatin interactions: a DFT-xTB study.

CONTEXT: A systematic study of hydrogen bonds in base pairs and the interaction of cisplatin with DNA fragments was carried out. Structure, binding energies, and electron density were analyzed. xTB has proven to be an accurate method for obtaining structures and binding energies in DNA structures. Our xTB values for DNA base binding energy were in the same order and in some cases better than CAM-B3LYP values compared to experimental values. Double-stranded DNA-cisplatin structures have been calculated and the hydrogen bonds of water molecules are a decisive factor contributing to the preference for the cisplatin-Guanine interaction. Higher values of the water hydrogen bonding energies were obtained in cisplatin-Guanine structures. Furthermore, the electrostatic potential was used to investigate and improve the analysis of DNA-cisplatin structures. METHODS: We applied the xTB method and the CAM-B3LYP functional combined with def2-SVP basis set to perform and analyze of the bonding energies of the cisplatin interaction and the effects of the hydrogen bonds. Results were calculated employing the xTB and the ORCA software.

Bifonazole caffeate: The first molecular salt of bifonazole with enhanced biopharmaceutical property based on experiments and quantum chemistry research.

In order to make novel breakthroughs in molecular salt studies of BCS class-IV antifungal medication bifonazole (BIF), a salification-driven strategy towards ameliorating attributes and aiding augment efficiency is raised. This strategy fully harnesses structural characters together attributes and benefits of caffeic acid (CAF) to concurrently enhance dissolvability and permeability of BIF by introducing the two ingredients into the identical molecular salt lattice through the salification reaction, which, coupled with the aroused potential activity of CAF significantly amplifies the antifungal efficacy of BIF. Guided by this route, the first BIF-organic molecular salt, BIF-CAF, is directionally designed and synthesized with satisfactorily structural characterizations and integrated theoretical and experimental explorations on the pharmaceutical properties. Single-crystal X-ray diffraction resolving confirms that there is a lipid-water amphiphilic sandwich structure constructed by robust charge-assistant hydrogen bonds in the salt crystal, endowing the molecular salt with the potential to enhance both dissolvability and permeability relative to the parent drug, which is validated by experimental evaluations. Remarkably, the comprehensive DFT-based theoretical investigations covering frontier molecular orbital, molecular electrostatic potential, Hirshfeld surface analysis, reduced density gradient, topology, sphericity and planarity analysis strongly support these observations, thereby allowing some positive relationships between macroscopic properties and microstructures of the molecular salt can be made. Intriguingly, the optimal properties, together with the stimulated activity of CAF markedly augment in vitro antifungal ability of the molecular salt, with magnifying inhibition zones and reducing minimum inhibitory concentrations. These findings fill in the gaps on researches of BIF-organic molecular salt, and adequately exemplify the feasibility and validity by integrating theoretical and experimental approaches to resolve BIF's problems via the salification-driven tactic.

Assessment of Embedding Schemes in a Hybrid Machine Learning/Classical Potentials (ML/MM) Approach.

Machine learning (ML) methods have reached high accuracy levels for the prediction of in vacuo molecular properties. However, the simulation of large systems solely through ML methods (such as those based on neural network potentials) is still a challenge. In this context, one of the most promising frameworks for integrating ML schemes in the simulation of complex molecular systems are the so-called ML/MM methods. These multiscale approaches combine ML methods with classical force fields (MM), in the same spirit as the successful hybrid quantum mechanics-molecular mechanics methods (QM/MM). The key issue for such ML/MM methods is an adequate description of the coupling between the region of the system described by ML and the region described at the MM level. In the context of QM/MM schemes, the main ingredient of the interaction is electrostatic, and the state of the art is the so-called electrostatic-embedding. In this study, we analyze the quality of simpler mechanical embedding-based approaches, specifically focusing on their application within a ML/MM framework utilizing atomic partial charges derived in vacuo. Taking as reference electrostatic embedding calculations performed at a QM(DFT)/MM level, we explore different atomic charges schemes, as well as a polarization correction computed using atomic polarizabilites. Our benchmark data set comprises a set of about 80k small organic structures from the ANI-1x and ANI-2x databases, solvated in water. The results suggest that the minimal basis iterative stockholder (MBIS) atomic charges yield the best agreement with the reference coupling energy. Remarkable enhancements are achieved by including a simple polarization correction.

Effects of lactic acid and ascorbic acid electrostatic spraying on the physicochemical attributes and microbial diversity of beef aged at mild temperature (10 °C).

This study aimed to clarify the effect of electrostatic spraying of lactic acid (LE) and ascorbic acid (AE) on vacuum-packaged beef aged at 10 °C. The physicochemical attributes, flavor profiles, and microbial diversities were evaluated. Beef steaks were electrostatically sprayed twice with 4% LE, 0.5% AE, or a mixture of them (LAE). Afterward, the beef was vacuum-packaged and aged. All treated beef exhibited a decrease in quality and sensory scores over time. At the end of the study period, the total viable count (TVC) and the total volatile basic nitrogen values in the control group (7.34 log CFU/g and 15.52 mg/100 g, respectively) were higher than those in the acid-treated groups. The LAE group exhibited the best color stability and the lowest TVC and Enterobacteriaceae counts after aging. High-throughput sequencing analysis revealed that acid types and electrostatic spray could change the microbiota structure. Leuconostoc was the dominant bacteria in the AE and LAE groups, while Enterococcus became the predominant bacteria in the NLE and LE groups with aging. This indicates that electrostatic spray combined with acid treatment can ensure beef quality and microbiological safety at mild temperatures.

PIP2 Is An Electrostatic Catalyst for Vesicle Fusion by Lowering the Hydration Energy: Arresting Vesicle Fusion by Masking PIP2.

Lipids are key factors in regulating membrane fusion. Lipids are not only structural components to form membranes but also active catalysts for vesicle fusion and neurotransmitter release, which are driven by soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) proteins. SNARE proteins seem to be partially assembled before fusion, but the mechanisms that arrest vesicle fusion before Ca2+ influx are still not clear. Here, we show that phosphatidylinositol 4,5-bisphosphate (PIP2) electrostatically triggers vesicle fusion as an electrostatic catalyst by lowering the hydration energy and that a myristoylated alanine-rich C-kinase substrate (MARCKS), a PIP2-binding protein, arrests vesicle fusion in a vesicle docking state where the SNARE complex is partially assembled. Vesicle-mimicking liposomes fail to reproduce vesicle fusion arrest by masking PIP2, indicating that native vesicles are essential for the reconstitution of physiological vesicle fusion. PIP2 attracts cations to repel water molecules from membranes, thus lowering the hydration energy barrier.

Nucleic acid liquids.

The confluence of recent discoveries of the roles of biomolecular liquids in living systems and modern abilities to precisely synthesize and modify nucleic acids (NAs) has led to a surge of interest in liquid phases of NAs. These phases can be formed primarily from NAs, as driven by base-pairing interactions, or from the electrostatic combination (coacervation) of negatively charged NAs and positively charged molecules. Generally, the use of sequence-engineered NAs provides the means to tune microsopic particle properties, and thus imbue specific, customizable behaviors into the resulting liquids. In this way, researchers have used NA liquids to tackle fundamental problems in the physics of finite valence soft materials, and to create liquids with novel structured and/or multi-functional properties. Here, we review this growing field, discussing the theoretical background of NA liquid phase separation, quantitative understanding of liquid material properties, and the broad and growing array of functional demonstrations in these materials. We close with a few comments discussing remaining open questions and challenges in the field.

Influence of an Intrinsically Disordered Region on Protein Domains Revealed by NMR-Based Electrostatic Potential Measurements.

Many human proteins possess intrinsically disordered regions containing consecutive aspartate or glutamate residues ("D/E repeats"). Approximately half of them are DNA/RNA-binding proteins. In this study, using nuclear magnetic resonance (NMR) spectroscopy, we investigated the electrostatic properties of D/E repeats and their influence on folded domains within the same protein. Local electrostatic potentials were directly measured for the HMGB1 protein, its isolated D/E repeats, and DNA-binding domains by NMR. The data provide quantitative information about the electrostatic interactions between distinct segments of HMGB1. Due to the interactions between the D/E repeats and the DNA-binding domains, local electrostatic potentials of the DNA-binding domains within the full-length HMGB1 protein were largely negative despite the presence of many positively charged residues. Our NMR data on counterions and electrostatic potentials show that the D/E repeats and DNA have similar electrostatic properties and compete for the DNA-binding domains. The competition promotes dissociation of the protein-DNA complex and influences the molecular behavior of the HMGB1 protein. These effects may be general among the DNA/RNA-binding proteins with D/E repeats.

Acceptor-donor-acceptor-type molecules with large electrostatic potential difference for effective NIR photothermal therapy.

Although acceptor-donor-acceptor (A-D-A)-type molecules offer advantages in constructing NIR absorbing photothermal agents (PTAs) due to their strong intramolecular charge transfer and molecular planarity, their applications in photothermal therapy (PTT) of tumors remain insufficiently explored. In particular, the influence of ESP distribution on the optical properties of A-D-A photosensitizers has not been investigated. Herein, we analyze and compare the difference in ESP distribution between A-D-A-type small molecules and polymers to construct NIR absorbing PTAs with a high extinction coefficient (ε) and high photothermal conversion efficiency (PCE). The calculation results of density functional theory (DFT) indicate that the large ESP difference makes A-D-A-type small molecules superior to their polymer counterparts in realizing tight molecular packing and strong NIR absorbance. Among the as-prepared nanoparticles (NPs), Y6 NPs exhibited an obvious bathochromic shift of absorption peak from 711 nm to 822 nm, with the NIR-II emission extended to 1400 nm. Moreover, a high ε value of 5.69 L g-1 cm-1 and a PCE of 66.3% were attained, making Y6 NPs suitable for PTT. With a concentration of 100 µg mL-1, Y6 NPs in aqueous dispersion yielded a death rate of 93.4% for 4T1 cells upon 808 nm laser irradiation (1 W cm-2) for 10 min, which is comparable with the best results of recently reported PTT agents.

Phosphate uptake in PhoX: Molecular mechanisms.

PhoX is a high-affinity phosphate binding protein, present in Xanthomonas citri, a phytopathogen responsible for the citrus canker disease. Performing molecular dynamics simulations and different types of computational analyses, we study the molecular mechanisms at play in relation to phosphate binding, revealing the global functioning of the protein: PhoX naturally oscillates along its global normal modes, which allow it to explore both bound and unbound conformations, eventually attracting a nearby negative phosphate ion to the highly positive electrostatic potential on its surface, particularly close to the binding pocket. There, several hydrogen bonds are formed with the two main domains of the structure. Phosphate creates, in this way, a strong bridge that connects the domains, keeping itself between them, in a tight closed conformation, explaining its high binding affinity.

Electrostatic interactions mediated defibrillation of ß-lactoglobulin fibrils using Keggin Polyoxometalates.

The whey protein ß-lactoglobulin (ßLG) forms fibrils similar to the amyloid fibrils in the neurodegenerative diseases due to its higher predisposition of ß-sheets. This study shed light on the understanding different inorganic Keggin polyoxometalates (POMs) interaction with the protein ßLG fibrils. POMs such as Phosphomolybdic acid (PMA), silicomolybdic acid (SMA), tungstosilicic acid (TSA), and phosphotungstic acid (PTA) were used due to their inherent higher anionic charges. The interaction studies were monitored with fluorescence spectra and Thioflavin T assay for both the ßLG monomers and the fibrils initially to elucidate the binding ability of the POMs. The binding of POMs and ßLG is also demonstrated by molecular docking studies. Zeta potential studies showed the electrostatic mediated higher interactions of the POMs with the protein fibrils. Isothermal titration calorimetry (ITC) studies showed that the molybdenum containing POMs have higher affinity to the protein fibrils than the tungsten. This study could help understanding formation of food grade protein fibrils which have profound importance in food industries.

Coordinate-Free and Low-Order Scaling Machine Learning Model for Atomic Partial Charge Prediction for Any Size of Molecules.

The atomic partial charge is of great importance in many fields, such as chemistry and drug-target recognition. However, conventional quantum-based computing of atomic charges is relatively slow, limiting further applications of atomic charge analysis. With the help of machine learning methods, various kinds of models appear to speed up atomic charge calculations. However, there are still some concerning problems. Some models based on geometric coordinates require high-accuracy geometry optimization as a preprocess, while other models have a limitation on the size of input molecules that narrow the applications of the model. Here, we propose a machine learning atomic charge model based on a message-passing featurizer. This preprocessing featurizer can quickly extract atomic environment information from a molecule according to the connectivity inside the molecule. The resulting descriptor can be used with a neural network to quickly predict the atomic partial charge. The model is able to automatically adapt to any size of molecule while remaining efficient and achieves a root-mean-square error in the Hirshfeld charge prediction of 0.018e, with an overall time complexity of O(n2). Thus, this model could enlarge the range of applications of atomic partial charge to more fields and cases.

Effect of Peptide-Polymer Host-Guest Electrostatic Interactions on Self-Assembling Peptide Hydrogels Structural and Mechanical Properties and Polymer Diffusivity.

Peptide-based supramolecular hydrogels are an attractive class of soft materials for biomedical applications when biocompatibility is a key requirement as they exploit the physical self-assembly of short self-assembling peptides avoiding the need for chemical cross-linking. Based on the knowledge developed through our previous work, we designed two novel peptides, E(FKFE)2 and K(FEFK)2, that form transparent hydrogels at pH 7. We characterized the phase behavior of these peptides and showed the clear link that exists between the charge carried by the peptides and the physical state of the samples. We subsequently demonstrate the cytocompatibility of the hydrogel and its suitability for 3D cell culture using 3T3 fibroblasts and human mesenchymal stem cells. We then loaded the hydrogels with two polymers, poly-l-lysine and dextran. When polymer and peptide fibers carry opposite charges, the size of the elemental fibril formed decreases, while the overall level of fiber aggregation and fiber bundle formation increases. This overall network topology change, and increase in cross-link stability and density, leads to an overall increase in the hydrogel mechanical properties and stability, i.e., resistance to swelling when placed in excess media. Finally, we investigate the diffusion of the polymers out of the hydrogels and show how electrostatic interactions can be used to control the release of large molecules. The work clearly shows how polymers can be used to tailor the properties of peptide hydrogels through guided intermolecular interactions and demonstrates the potential of these new soft hydrogels for use in the biomedical field in particular for delivery or large molecular payloads and cells as well as scaffolds for 3D cell culture.